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Gene coexpression analysis in Arabidopsis thaliana based on public microarray data.

ABSTRACT: Coexpressed genes tend to participate in related biological processes. Gene coexpression analysis allows the discovery of functional gene partners or the assignment of biological roles to genes of unknown function. In this protocol, we describe the steps necessary to create a gene coexpression tree for Arabidopsis thaliana, using publicly available Affymetrix CEL microarray data. Because the computational analysis described here is highly dependent on sample quality, we detail an automatic quality control approach. For complete details on the use and execution of this protocol, please refer to Zogopoulos et al. (2021).

SUBMITTER: Zogopoulos VL

PROVIDER: S-EPMC8885756 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature

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Gene coexpression analysis in <i>Arabidopsis thaliana</i> based on public microarray data.

Zogopoulos Vasileios L VL Malatras Apostolos A Michalopoulos Ioannis I

STAR protocols 20220226 1

Coexpressed genes tend to participate in related biological processes. Gene coexpression analysis allows the discovery of functional gene partners or the assignment of biological roles to genes of unknown function. In this protocol, we describe the steps necessary to create a gene coexpression tree for <i>Arabidopsis thaliana</i>, using publicly available Affymetrix CEL microarray data. Because the computational analysis described here is highly dependent on sample quality, we detail an automati ...[more]

PMID: 35243384

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Project description:IntroductionIncreasing global warming has made heat stress a serious threat to crop productivity and global food security in recent years. One of the most promising solutions to address this issue is developing heat-stress-tolerant plants. Hence, a thorough understanding of heat stress response mechanisms, particularly molecular ones, is crucial.MethodsAlthough numerous studies have used microarray expression profiling technology to explore this area, these experiments often face limitations, leading to inconsistent results. To overcome these limitations, a random effects meta-analysis was employed using advanced statistical methods. A meta-analysis of 16 microarray datasets related to heat stress response in Arabidopsis thaliana was conducted.ResultsThe analysis revealed 1,972 significant differentially expressed genes between control and heat-stressed plants (826 over-expressed and 1,146 down-expressed), including 128 differentially expressed transcription factors from different families. The most significantly enriched biological processes, molecular functions, and KEGG pathways for over-expressed genes included heat response, mRNA splicing via spliceosome pathways, unfolded protein binding, and heat shock protein binding. Conversely, for down-expressed genes, the most significantly enriched categories included cell wall organization or biogenesis, protein phosphorylation, transmembrane transporter activity, ion transmembrane transporter, biosynthesis of secondary metabolites, and metabolic pathways.DiscussionThrough our comprehensive meta-analysis of heat stress transcriptomics, we have identified pivotal genes integral to the heat stress response, offering profound insights into the molecular mechanisms by which plants counteract such stressors. Our findings elucidate that heat stress influences gene expression both at the transcriptional phase and post-transcriptionally, thereby substantially augmenting our comprehension of plant adaptive strategies to heat stress.

Project description:BACKGROUND:Alternaria blight, a recalcitrant disease caused by Alternaria brassicae and Alternaria brassicicola, has been recognized for significant losses of oilseed crops especially rapeseed-mustard throughout the world. Till date, no resistance source is available against the disease; hence, plant breeding methods cannot be used to develop disease-resistant varieties. Therefore, in the present study, efforts have been made to identify resistance and defense-related genes as well as key components of JA-SA-ET-mediated pathway involved in resistance against Alternaria brasscicola through computational analysis of microarray data and network biology approach. Microarray profiling data from wild type and mutant Arabidopsis plants challenged with Alternaria brassicicola along with control plant were obtained from the Gene Expression Omnibus (GEO) database. The data analysis, including DEGs extraction, functional enrichment, annotation, and network analysis, was used to identify genes associated with disease resistance and defense response. RESULTS:A total of 2854 genes were differentially expressed in WT9C9; among them, 1327 genes were upregulated and 1527 genes were downregulated. A total of 1159 genes were differentially expressed in JAM9C9; among them, 809 were upregulated and 350 were downregulated. A total of 2516 genes were differentially expressed in SAM9C9; among them, 1355 were upregulated and 1161 were downregulated. A total of 1567 genes were differentially expressed in ETM9C9; among them, 917 were upregulated and 650 were downregulated. Besides, a total of 2965 genes were differentially expressed in contrast WT24C24; among them, 1510 genes were upregulated and 1455 genes were downregulated. A total of 4598 genes were differentially expressed in JAM24C24; among them, 2201 were upregulated and 2397 were downregulated. A total of 3803 genes were differentially expressed in SAM24C24; among them, 1819 were upregulated and 1984 were downregulated. A total of 4164 genes were differentially expressed in ETM24C24; among them, 1895 were upregulated and 2269 were downregulated. The upregulated genes of Arabidopsis thaliana were mapped and annotated with CDS sequences of Brassica rapa obtained from PlantGDB database. Additionally, PPI network of these genes were constructed to investigate the key components of hormone-mediated pathway involved in resistance during pathogenesis. CONCLUSION:The obtained information from present study can be used to engineer resistance to Alternaria blight caused by Alternaria brasscicola through molecular breeding or genetic manipulation-based approaches for improving Brassica oilseed productivity.

Dataset Information

Gene coexpression analysis in Arabidopsis thaliana based on public microarray data.

Publications

Gene coexpression analysis in <i>Arabidopsis thaliana</i> based on public microarray data.

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